Looking at the numbers

Data Sources

For weather data…

For outcomes data, we are interested in the incidence of asthma, skin cancer and lung cancer across time and space. We obtained age-adjusted incidence rates data for these three health outcomes for the U.S. states New York, Ohio and Pennsylvania over multiple years. The following bullet points provide links from where we obtained the data.

• Asthma
  • Provide source
• Melanoma of the skin (skin cancer)
  • New York
  • Ohio
  • Pennsylvania
• Lung cancer
  • New York
  • Ohio
  • Pennsylvania

We also obtained age-adjusted incidence rates data for these three health outcomes for the U.S. states New York, Ohio and Pennsylvania at the county-level at fixed time points. The following bullet points provide links from where we obtained the data. The asthma data is provided for the year 2016 and the skin cancer and lunger cancer data is average over the years 2014-2018.

• Asthma
  • Provide source
• Melanoma of the skin (skin cancer) and lung cancer
  • All 50 states

Each of these data sets were exported and each imported into R. For each of the three health outcomes, the data sets were merged across the three states for the longitudinal data and for the cross-sectional data. This effort resulted in six data sets. The data import and cleaning of the original data can be found in the data import folder on our github repository.

We will now import the six data sets and merge all longitudinal data together and merge all cross-sectional data together to have two data sets.

Let’s talk health outcomes:

To discuss how climate change has impacted the rate of certain negative health outcomes, let’s first assess their general prevalence.

Recent County-Level Trends

Clearly, according to the map below, lung cancer is a relevant issue in our three states of interest (NY, PA, and OH). They also provide a good range of examples, as we can see multiple counties with high age-adjusted incidence rates in Ohio, a few in New York, and virtually none in Pennsylvania.

# plotly of county level data

county_map_lc

Recent State Level Trends

We can also check how these rates have changed by state over time:

# plotly of county level data

fig

state_mel_plot